1. Field
The present disclosure relates generally to an improved data processing system and in particular, to a method and apparatus for processing data. Still more particularly, the present disclosure relates to a method, apparatus, and computer program product for measuring height in a perspective image.
2. Background
Images of a scene may be generated using various types of sensors. These sensors include, for example, forward looking infrared cameras, synthetic aperture radar systems, video cameras, and other suitable types of sensors. It may be desirable to make measurements of a feature in the image of a scene. Two-dimensional images, however, are unable to convey more than two dimensions of information such as width and depth.
Two-dimensional images also present a perspective distortion due to the means by which they were acquired. For images formed using a lens, such as video cameras or forward looking infrared cameras, this distortion is called perspective. Perspective appears as a scale increase for portions of the image that are closer to the sensor, and a decrease for portions of the image that are more distant. For synthetic aperture radar, the distortion is related to relative heights of the different parts of a scene. Higher parts of the scene are positioned closer to the sensor in the image than lower parts, an effect called foreshortening.
A two-dimensional image, however, may be registered with a spatial model that describes a three-dimensional shape of surfaces in the scene depicted in the image. With registration, individual pixels in the image can be associated with specific three-dimensional locations in the spatial model of the scene. The association is provided by a projection transformation or an inverse projection transformation.
One issue with this type of technique is that sufficiently accurate three-dimensional models of scenes may not be easy to obtain. A model of a scene may include a digital elevation matrix (DEM). A digital elevation matrix is a two-dimensional array of values describing a third coordinate dimension on a scene surface. The values describing elements within the matrix correspond to a location on the surface of the scene. In other words, the values may identify a particular element that contains a value about the location in the scene.
One common example of this type of model provides array locations in a row and column system that is associated with horizontal longitude and latitude locations in the scene. The value at each location in this array is an elevation that is found at that particular latitude and longitude location in the scene. If a location on the surface of the scene cannot be measured for an elevation value or cannot be measured accurately, the corresponding value describing the element for that location is either missing or inaccurate.
This type of association to a three-dimensional model is referred to as being spatially coded. When the scene coordinates are for a geographic coordinate system, this type of model may be referred to as a geocoded or georegistered model or as a geocoded elevation database.
For example, with natural scenes, the model for these scenes is sometimes obtained using a stereo image correlation technique. This type of technique, however, is unable to capture small elevation details or some types of vertical features with accuracy. Edges of vertical faces may be rounded, and small features may be lost entirely or only appear as small lumps. The sharp discontinuities in the surface may cause dissimilarities in the stereo images that may defeat the stereo correlation process for that particular object.
Further, stereo imagery and the amount of data needed to retain the scene model for this technique may also result in these models having a lower spatial resolution for array locations. In other words, the array may cover a larger area of the scene with fewer elevation measurements. Also, these models may be edited to remove some surface detail. For example, a digital terrain elevation database (DTED) available from the United States Government is an example of a geocoded elevation database in which only bare-earth elevations are represented. Thus, tree coverage, buildings, and other vertical features may be removed as contributors to elevation values. These types of models, however, are readily available at no or little cost.
As a result, these types of models do not provide an accurate representation of all features on a surface. These models may provide elevation for the ground, but may not include various vertical features. These vertical features may include, for example, without limitation, trees, towers, buildings, trucks, or other objects that may have elevations.
For example, a digital elevation model may include elevation information for a mountain. A tower on the mountain, however, may not be included in the digital elevation model. As a result, an image of the mountain with the tower cannot be used to obtain a measurement to identify a location of the top of the tower.
As a result, identifying locations in a scene corresponding to an image of the scene may be difficult to perform. For example, if the feature is a tree, a building, or some other object not taken into account in the digital elevation model, the location of those objects cannot be accurately identified even with registration of the image to the digital elevation model.
Therefore, it would be advantageous to have an improved method and apparatus for height measurement in an image.